TOUCHDOWN: Natural Language Navigation and Spatial Reasoning in Visual Street Environments
We study the problem of jointly reasoning about language and vision through a navigation and spatial reasoning task. We introduce the Touchdown task and dataset, where an agent must first follow navigation instructions in a Street View environment to a goal position, and then guess a location in its...
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| Published in: | Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) pp. 12530 - 12539 |
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| Main Authors: | , , , , |
| Format: | Conference Proceeding |
| Language: | English |
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IEEE
01.06.2019
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| ISSN: | 1063-6919 |
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| Abstract | We study the problem of jointly reasoning about language and vision through a navigation and spatial reasoning task. We introduce the Touchdown task and dataset, where an agent must first follow navigation instructions in a Street View environment to a goal position, and then guess a location in its observed environment described in natural language to find a hidden object. The data contains 9326 examples of English instructions and spatial descriptions paired with demonstrations. We perform qualitative linguistic analysis, and show that the data displays a rich use of spatial reasoning. Empirical analysis shows the data presents an open challenge to existing methods. |
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| AbstractList | We study the problem of jointly reasoning about language and vision through a navigation and spatial reasoning task. We introduce the Touchdown task and dataset, where an agent must first follow navigation instructions in a Street View environment to a goal position, and then guess a location in its observed environment described in natural language to find a hidden object. The data contains 9326 examples of English instructions and spatial descriptions paired with demonstrations. We perform qualitative linguistic analysis, and show that the data displays a rich use of spatial reasoning. Empirical analysis shows the data presents an open challenge to existing methods. |
| Author | Suhr, Alane Chen, Howard Artzi, Yoav Misra, Dipendra Snavely, Noah |
| Author_xml | – sequence: 1 givenname: Howard surname: Chen fullname: Chen, Howard organization: Cornell – sequence: 2 givenname: Alane surname: Suhr fullname: Suhr, Alane organization: Cornell Univ – sequence: 3 givenname: Dipendra surname: Misra fullname: Misra, Dipendra organization: Cornell Univ – sequence: 4 givenname: Noah surname: Snavely fullname: Snavely, Noah organization: Cornell Univ. and Google AI – sequence: 5 givenname: Yoav surname: Artzi fullname: Artzi, Yoav organization: Cornell Univ |
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| Snippet | We study the problem of jointly reasoning about language and vision through a navigation and spatial reasoning task. We introduce the Touchdown task and... |
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| SubjectTerms | Cognition Data collection Datasets and Evaluation Linguistics Navigation Spatial databases Urban areas Vision + Language Visual Reasoning Visualization |
| Title | TOUCHDOWN: Natural Language Navigation and Spatial Reasoning in Visual Street Environments |
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